Abstract
In the modern world, with the rapid technological advancements in the field of electricity, innovative techniques are being employed to optimize electric power generation. These techniques involve a combination of conventional energy sources (coal, gas, etc.) with Renewable Energy Sources (RES) (PV, wind, etc.) to meet the electric power demands. Unfortunately, the intermittent nature of these RES has a detrimental effect on the system's power quality. To counter this issue, an efficient, intelligent, and advanced control method that employs a Model Predictive Controller (MPC) in parallel with Fractional Order Proportional Integral Controller (FOPI) is proposed for Load Frequency Control (LFC) of the connected power system. With the help of this controller, an optimum solution for this problem is established in this study to enhance the power quality of the overall system by reducing the frequency fluctuations in the system. In the end, system responses to load changes have been analyzed and compared with those of state-of-the-art controllers like the Firefly Algorithm (FA) tuned PI, the Genetic Algorithm (GA) tuned PI, and MPC tuned PI to show the adequacy of the proposed controller.
| Original language | English |
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| Title of host publication | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350347074 |
| DOIs | |
| State | Published - 2023 |
| Event | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 - Rome, Italy Duration: 10 May 2023 → 12 May 2023 |
Publication series
| Name | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
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Conference
| Conference | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
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| Country/Territory | Italy |
| City | Rome |
| Period | 10/05/23 → 12/05/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Fractional Order Proportional Integral Controller
- Load Frequency Control
- Model Predictive Controller
- Renewable Energy Sources
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality
- Control and Optimization